While acoustic side channel attacks have not been explored for robotic systems,
enhancing the novelty of this work, there has been previous research in the
area of acoustic side channels.
In a similar respect to robotics, the exploration of information leakage in the
acoustic side channel has been explored for 3D printers [1]}
– some of which making use of smartphones to carry out the
attack [2]}, [3]} – and additive manufacturing
systems [4]}. However, many of these attacks solely
focus on IP theft. The acoustic side channel attack presented in this work
focus solely on the movement of the robot arm and the compromise of operational
confidentiality, which when looking at the bigger picture is much more valuable
to an attacker. Furthermore, the reconstruction of G-code is an unnecessary
extra step as movements which correspond to these can be inferred from individual
movement fingerprinting under the assumption the robot is operated by an Arduino.
Furthermore, while the robot in this work is operated by an Arduino, the focus
is on reconstructing movements from the acoustic emanations, irrespective of the
microcontroller used and thus applies to robotic systems in general and not
those restricted to being operated by an Arduino.
